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基于深度置信网络效能拟合的火控系统精度全局敏感性分析

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针对当前航空火控系统的精度研究对数据完备性要求较高,且仅能分析系统内单误差源影响因素的问题,提出一种全新的基于深度置信网络(Deep Belief Network,DBN)效能拟合的火控系统精度全局敏感性分析(Global Sensitivity Analysis via Deep Belief Network,GSADBN)算法.从全局敏感性分析算法的优劣点出发,分析传统的全局敏感性分析算法在不完备数据下存在的局限性.利用DBN优异的特征提取能力,并采用无监督训练和有监督微调相结合的算法,搭建并训练火控系统效能拟合模型.研究结果表明:与传统Sobol算法、经典傅里叶振幅敏感性检验(Fourier Amplitude Sensitivity Test,FAST)算法以及最新的基于贝叶斯网络的 Sobol(Bayesian Neural Sobol,BNSobol)算法相比,GSADBN算法不仅可以满足精度要求,同时还可以在不完备数据下达到传统算法在完备数据下精度分析的效果;该算法可以在火控系统不完备数据下取得较好的精度分析结果,同时在设计火控系统各模块时,给出精度方面的合理方案,从而为火控系统的设计及作战效能的提高提供参考和理论支撑.
Global Sensitivity Analysis on Accuracy of Aviation Fire Control System via DBN Effectiveness Fitting
In view of the fact that most of the current researches on the accuracy of fire control system require high data integrity and only analyze the influence factors of single error source,this paper proposes a novel global sensitivity analysis(GSA)method based on deep belief network(DBN)effectiveness fitting for the accuracy of fire control system.Starting from the advantages and disadvantages of the traditional GSA methods,the limitations of the traditional methods in the case of incomplete data are analyzed.Then,a fire control system performance fitting model is constructed and trained by utilizing the excellent feature extraction ability of DBN and a combination of unsupervised training and supervised fine-tuning methods.The proposed GSADBN method is compared with traditional Sobol method,classical Fourier amplitude sensitivity test(FAST)method and improved BNSobol method.The experimental results show that the proposed GSADBN method can not only meet the accuracy requirements,but also obtain the excellent accuracy analysis results when the data from aviation fire control system is incomplete.Furthermore,GSADBN method can give a reasonable scheme of accuracy value when designing each module of fire control system,so as to provide reference and theoretical support for the design of fire control system and the improvement of combat effectiveness.

aviation fire control systemdeep belief networkGSADBN methodaccuracy assessmentglobal sensitivity analysis

汪强龙、高晓光、李新宇、闫栩辰、万开方

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西北工业大学电子信息学院,陕西西安 710129

航空火控系统 深度置信网络 GSADBN算法 精度评估 全局敏感性分析

国家自然科学基金项目陕西省重点研发计划项目中央高校基本科研业务费专项项目电磁空间作战与应用重点实验室基金项目西安市科技计划项目

620032672023-GHZD-33G2022KY06022022ZX009021RGZN0016

2024

10.12382/bgxb.2023.0659

兵工学报
中国兵工学会

兵工学报

CSTPCD北大核心
影响因子：0.735
ISSN：1000-1093
年,卷(期)：2024.45(10)